Data Is the New Content

In this special guest feature, Moshe Kranc, CTO at the tech consulting firm Ness, discusses how big industry players will increasingly try to corner the market on high quality one-of-a-kind data that can yield actionable insights – unseating content as king.Moshe has extensive experience in leading adoption of bleeding edge technologies, having worked for large companies as well as entrepreneurial start-ups. Moshe previously headed the Big Data Centre of Excellence at Barclays’ Israel Development Centre (IDEC). Moshe has worked in the high tech industry for over 30 years in the United States and Israel. He was part of the Emmy award-winning team that designed the scrambling system for DIRECTV, and he holds 6 patents in areas related to pay television, computer security and text mining. He has led R&D teams at companies such as Zoomix (purchased by Microsoft) and NDS (purchased by Cisco). He is a graduate of Brandeis University and earned graduate degrees from both the University of California at Berkeley and Boston University.

IBM made headlines recently when it purchased the data collection services of The Weather Channel for an undisclosed amount. At first blush, this seems to be an odd combination: IBM sells mainframes and software services, not weather predictions. To understand this move, we need to look at an analogous trend: the rise and fall of content.

For many years I developed conditional access systems for pay TV, to ensure that only paying customers could view premium content. The technology was fascinating, and I learned a lot about the business of broadcasters like DirecTV, Star, BSkyB and Cablevision. But, everyone in the industry realized that the technology and the distribution network were secondary in importance to the content. Broadcasters who could land rights to the best content – the blockbuster movies, the hottest premium channels like HBO, the best lifestyle content for cooking and fashion – would win the most subscribers. Content was king, because there were only a few premium content providers.

A similar process took place on the Internet. Google ruled the roost thanks to search, but there was only a handful of premium content sites. In the travel domain, for example, Michelin and Frommer’s always showed up in the top 5 results for vacation queries, because they had built up their brand equity over decades. That’s why Google went on a buying spree, gobbling up iconic content sites like Frommer’s and Zagat. All content is not created equal – some content is so authoritative and venerated that it acts as a barrier to entry to any potential newcomers. Buy that content, reasoned Google, and you keep your high value users within your walled garden, where you can target high-value ads at them.

Over time, content was unseated from its position as king. Today, there are many alternatives to any high quality content (for example, HBO has competition from Showtime, Netflix and Amazon), and user-generated content in areas like finance and sports competes head to head with premium pay content.

We are witnessing the start of a similar process for data. The Internet of Things and Big Data Analytics have led many companies to the realization that their most valuable asset may not be their current product line, but rather the data they collect about their customers. For example, an airline booking company, besides collecting a commission on every booking, is sitting on a gold mine of data about traveler behavior, data that many travel-related companies (e.g., hotels, restaurants, tour companies) would pay a lot to access and analyze. Like content in its time, not all data is created equal. Some companies have invested years building up a data collection network that yields high quality data. The existence of such a resource serves as a barrier to entry for any newcomer.

The Weather Channel is a great example of this. Their products are a TV station and a web site that provide accurate weather forecasts to users. Monetizing these products has always been challenging – the TV station is usually part of a broadcast bundle that earns The Weather Channel pennies per thousand subscribers, and the web site is relatively light on advertising. But The Weather Channel’s data collection network? That’s a one-of-a-kind asset, built up over years, which collects weather information from thousands of sources, to a level of granularity that is unsurpassed. That network is unique – it took years to build, and its existence effectively blocks any competitor from building a similar network.

The value of accurate weather data is immense, not just for consumers, but also for the enterprise. Most businesses are affected by the weather, e.g., retail traffic decreases during storms, spring-like weather brings out home buyers. Companies will pay a lot for micro-accurate weather predictions, based on The Weather Channel’s fine-grained weather data. Like content in its time, this data is king.

IBM seems to have realized the potential of high quality data before the other giants. Having developed the Watson technology to analyze Big Data, IBM now seems to be going after high-value data that Watson can turn into insights. Just as Google in their time bought up premium content, IBM seems to be buying up premium data. Expect this trend to grow as data monetization gains popularity – big players will increasingly try to corner the market on high quality one-of-a-kind data that can yield actionable insights. In 2016, data has unseated content as king.

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